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» An e-Process Selection Model
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LSO
2004
Springer
16 years 2 days ago
COTS Evaluation Supported by Knowledge Bases
Selection of Commercial-off-The-Shelf (COTS) software products is a knowledge-intensive process. In this paper, we show how knowledge bases can be used to facilitate the COTS selec...
Abdallah Mohamed, Tom Wanyama, Günther Ruhe, ...
KDD
1999
ACM
237views Data Mining» more  KDD 1999»
15 years 11 months ago
Using Association Rules for Product Assortment Decisions: A Case Study
It has been claimed that the discovery of association rules is well-suited for applications of market basket analysis to reveal regularities in the purchase behaviour of customers...
Tom Brijs, Gilbert Swinnen, Koen Vanhoof, Geert We...
KDD
2000
ACM
142views Data Mining» more  KDD 2000»
15 years 10 months ago
Automating exploratory data analysis for efficient data mining
Having access to large data sets for the purpose of predictive data mining does not guarantee good models, even when the size of the training data is virtually unlimited. Instead,...
Jonathan D. Becher, Pavel Berkhin, Edmund Freeman
201
Voted
KDD
2010
ACM
310views Data Mining» more  KDD 2010»
15 years 10 months ago
An integrated machine learning approach to stroke prediction
Stroke is the third leading cause of death and the principal cause of serious long-term disability in the United States. Accurate prediction of stroke is highly valuable for early...
Aditya Khosla, Yu Cao, Cliff Chiung-Yu Lin, Hsu-Ku...
GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
15 years 7 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...